Introduction: Adverse effects of radiotherapy (RT) significantly affect patient's quality of life (QOL). The possibility to identify patient-related factors that are associated with individual radiosensitivity would optimize adjuvant RT treatment, limiting the severity of normal tissue reactions, and improving patient's QOL. In this study, we analyzed the relationships between genetic features and toxicity grading manifested by RT patients looking for possible biomarkers of individual radiosensitivity.Methods: Early radiation toxicity was evaluated on 143 oncological patients according to the Common Terminology Criteria for Adverse Events (CTCAE). An individual radiosensitivity (IRS) index defining four classes of radiosensitivity (highly radiosensitive, radiosensitive, normal, and radioresistant) was determined by a G2-chromosomal assay on ex vivo irradiated, patient-derived blood samples. The expression level of 15 radioresponsive genes has been measured by quantitative real-time PCR at 24 h after the first RT fraction, in blood samples of a subset of 57 patients, representing the four IRS classes.Results: By applying univariate and multivariate statistical analyses, we found that fatigue was significantly associated with IRS index. Interestingly, associations were detected between clinical radiation toxicity and gene expression (ATM, CDKN1A, FDXR, SESN1, XPC, ZMAT3, and BCL2/BAX ratio) and between IRS index and gene expression (BBC3, FDXR, GADD45A, and BCL2/BAX).Conclusions: In this prospective cohort study we found that associations exist between normal tissue reactions and genetic features in RT-treated patients. Overall, our findings can contribute to the identification of biological markers to predict RT toxicity in normal tissues.

Deep neck infections (DNI) spread along fascial planes and involve neck spaces. Very few studies have investigated potentially prognostic factors using multivariate statistical models. Our aim was to analyze 282 consecutive cases of DNI using multivariate (logistic) statistical models to identify independent significant factors influencing prognosis in terms of complications and long-term hospitalization (>6 days). In our series, only involvement of more than one neck space was independently significant in prognosticating complications of DNI (odds ratio [OR] 2.46). The presence of comorbidities (OR 2.13), non-odontogenic sites of origin (OR 1.88), leukocyte counts above 11.0 cells × 10(9)/L at presentation (OR 3.57), and the need for both medical and surgical treatments (OR 4.66) was significantly and independently prognostic of long hospital stays. Multivariate analysis can distinguish between risk factors and their relative contribution to outcome. The few published studies using multivariate models to analyze DNI prognosis considered quite large cohorts, but no clinical variables persistently revealed an independent significant prognostic role. This evidence seems to underscore the complex interdependence of several clinical variables in contributing to DNI prognosis, and the heterogeneity of the diagnostic/therapeutic approaches adopted.

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The immunohistochemical expression of TAZ (but not YAP or AREG) correlated significantly with schwannoma volume measured on ceMRI. Further investigations are needed to identify the biological factors influencing tumor proliferation (ideally secreted proteins like AREG) that might be detected using non-invasive approaches (i.e., blood samples).